Abstract
In this article, we consider a stochastic PDE of parabolic type, driven by a space-time white-noise, and its numerical discretization in time with a semi-implicit Euler scheme. When the nonlinearity is assumed to be bounded, then a dissipativity assumption is satisfied, which ensures that the SDPE admits a unique invariant probability measure, which is ergodic and strongly mixing—with exponential convergence to equilibrium. Considering test functions of class \(\mathcal{C}^2\), bounded and with bounded derivatives, we prove that we can approximate this invariant measure using the numerical scheme, with order 1/2 with respect to the time step.
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Bréhier, CE. Approximation of the Invariant Measure with an Euler Scheme for Stochastic PDEs Driven by Space-Time White Noise. Potential Anal 40, 1–40 (2014). https://doi.org/10.1007/s11118-013-9338-9
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DOI: https://doi.org/10.1007/s11118-013-9338-9
Keywords
- Stochastic partial differential equations
- Invariant measures and Ergodicity
- Weak approximation
- Euler scheme